Triple
T13088305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Air Koryo |
E310393
|
entity |
| Predicate | callsign |
P1565
|
FINISHED |
| Object | AIR KORYO |
E310393
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: AIR KORYO | Statement: [Air Koryo, callsign, AIR KORYO]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: AIR KORYO Context triple: [Air Koryo, callsign, AIR KORYO]
-
A.
Air Koryo
chosen
Air Koryo is the state-owned national airline of North Korea, known for its Soviet-era fleet and limited international operations.
-
B.
Nampo
Nampo is a major port city in southwestern North Korea, known for its industrial facilities and strategic location on the Yellow Sea.
-
C.
Sinuiju, Korea
Sinuiju, Korea is a North Korean city on the Yalu River bordering China, known as an important industrial and transportation hub.
-
D.
Pyongyang
Pyongyang is the capital and largest city of North Korea, serving as its political, economic, and cultural center.
-
E.
Air Seoul
Air Seoul is a South Korean low-cost airline based in Seoul that operates regional flights across East Asia.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d806a733548190989cfd4ce981ca33 |
completed | April 9, 2026, 8:05 p.m. |
| NER | Named-entity recognition | batch_69d981378dd08190b4f00e4e5df0e480 |
completed | April 10, 2026, 11:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6d614704481908758cf8691a941ea |
completed | May 3, 2026, 4:59 a.m. |
Created at: April 9, 2026, 9:02 p.m.